Yu Xiaolu, Li Hang, Zhang Jian Andrew, Huang Xiaojing, Cheng Zhiqun
School of Electronics and Information, Hangzhou Dianzi University, Hangzhou 310018, China.
The Global Big Data Technologies Centre, University of Technology Sydney, Sydney 2007, Australia.
Sensors (Basel). 2022 Jul 12;22(14):5207. doi: 10.3390/s22145207.
The millimeter wave (mmWave) channel is dominated by line-of-sight propagation. Therefore, the acquisition of angle-of-arrival (AoA) and polarization state of the wave is of great significance to the receiver. In this paper, we investigate AoA and polarization estimation in a mmWave system employing dual-polarized antenna arrays. We propose an enhanced AoA estimation method using a localized hybrid dual-polarized array for a polarized mmWave signal. The use of dual-polarized arrays greatly improves the calibration of differential signals and the signal-to-noise ratio (SNR) of the phase offset estimation between adjacent subarrays. Given the estimated phase offset, an initial AoA estimate can be obtained, and is then used to update the phase offset estimation. This leads to a recursive estimation with improved accuracy. We further propose an enhanced polarization estimation method, which uses the power of total received signals at dual-polarized antennas to compute the cross-correlation-to-power ratio instead of using only one axis dipole. Thus the accuracy of polarization parameter estimation is improved. We also derive a closed-form expression for mean square error lower bounds of AoA estimation and present an average SNR analysis for polarization estimation performance. Simulation results demonstrate the superiority of the enhanced AoA and polarization parameter estimation methods compared to the state of the art.
毫米波（mmWave）信道主要由视距传播主导。因此，获取波的到达角（AoA）和极化状态对接收机具有重要意义。在本文中，我们研究了采用双极化天线阵列的毫米波系统中的AoA和极化估计。我们提出了一种用于极化毫米波信号的增强型AoA估计方法，该方法使用局部混合双极化阵列。双极化阵列的使用极大地改善了差分信号的校准以及相邻子阵列之间相位偏移估计的信噪比（SNR）。给定估计的相位偏移，可以获得初始的AoA估计值，然后将其用于更新相位偏移估计。这导致了具有更高精度的递归估计。我们进一步提出了一种增强型极化估计方法，该方法使用双极化天线处总接收信号的功率来计算互相关与功率比，而不是仅使用一个轴偶极子。从而提高了极化参数估计的精度。我们还推导了AoA估计的均方误差下限的闭式表达式，并给出了极化估计性能的平均SNR分析。仿真结果证明了增强型AoA和极化参数估计方法相对于现有技术的优越性。
